Results 161 to 170 of about 641 (195)

A Fast Collocation Method for Solving Stochastic Integral Equations

SIAM Journal on Numerical Analysis, 2009
Based on sparse grid multiscale piecewise polynomial bases, we develop a fast collocation method for solving Fredholm integral equations of the second kind with stochastic loading terms. It is proved that the proposed method preserves the optimal rate of convergence and has linear (up to a logarithmic factor) computational complexity.
Yanzhao Cao, Bin Wu, Yuesheng Xu
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Towards Goal-Oriented Stochastic Design Employing Adaptive Collocation Methods

13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, 2010
Non-intrusive polynomial chaos expansion (NIPCE) methods based on orthogonal polynomials and stochastic collocation (SC) methods based on Lagrange interpolation polynomials are attractive techniques for uncertainty quantification (UQ) due to their strong mathematical basis and ability to produce functional representations of stochastic dependence. Both
Michael Eldred, Laura Swiler
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Stochastic collocation methods for aeroelastic system with uncertainty

2009
Computation methods based on the Wiener chaos expansion have been developed to study the behaviors of the aeroelastic system with randomparameters. It is proven that the discrete wavelet transformation is one ofthe most accurate and efficient numerical schemes for this uncertainty quantizationproblem.
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Stochastic collocation methods for differential equations with white noise

2017
Stochastic collocation methods can lead to a fully decoupled system of PDEs, which can be readily implemented on parallel computers. However, stochastic collocation methods do not work when longer time integration is required. Though these methods are also cursed by the dimensionality, we apply the recursive strategy for longer time integration ...
Zhongqiang Zhang, George Em Karniadakis
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Stochastic Collocation Method for Uncertainty Propagation

AIAA Guidance, Navigation, and Control Conference, 2012
Bin Jia, Sheng Cai, Yang Cheng, Ming Xin
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Evaluation of Designed Distributions for Stochastic Collocation Methods

AIAA SCITECH 2023 Forum, 2023
Edwin E. Forster, Daniel L. Clark, Philip Beran   +2 more
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Stochastic Collocation Method Applied to Transcranial Magnetic Stimulation Analysis

2016
This work examines the influence of the brain tissue parameters' uncertainty and the coil positioning variations within the framework of Transcranial Magnetic Stimulation (TMS). A combination of deterministic modeling and the stochastic theoretical basis was used in the assessment of the parameter uncertainties effects on the induced electric field and
Šušnjara Nejašmić, Anna, Poljak, Dragan, Cvetković, Mario   +2 more
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Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians

Ca-A Cancer Journal for Clinicians, 2022
William A Hal, X Allen Li, Daniel A Low
exaly  

Muti-fidelity Stochastic Collocation methods using Model Reduction techniques

2013
Over the last few years there have been dramatic advances in our understanding of mathematical and computational models of complex systems in the presence of uncertainty. This has led to a growth in the area of uncertainty quantification as well as the need to develop efficient, scalable, stable and convergent computational methods for solving ...
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Stochastic collocation enhanced line sampling method for reliability analysis

Reliability Engineering & System Safety, 2023
Ning Wei, Zhenzhou Lu, Yingshi Hu
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